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Mobile Artificial Intelligence Projects

You're reading from   Mobile Artificial Intelligence Projects Develop seven projects on your smartphone using artificial intelligence and deep learning techniques

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789344073
Length 312 pages
Edition 1st Edition
Languages
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Authors (3):
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Arun Padmanabhan Arun Padmanabhan
Author Profile Icon Arun Padmanabhan
Arun Padmanabhan
Karthikeyan NG Karthikeyan NG
Author Profile Icon Karthikeyan NG
Karthikeyan NG
Matt Cole Matt Cole
Author Profile Icon Matt Cole
Matt Cole
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Toc

Table of Contents (12) Chapters Close

Preface 1. Artificial Intelligence Concepts and Fundamentals FREE CHAPTER 2. Creating a Real-Estate Price Prediction Mobile App 3. Implementing Deep Net Architectures to Recognize Handwritten Digits 4. Building a Machine Vision Mobile App to Classify Flower Species 5. Building an ML Model to Predict Car Damage Using TensorFlow 6. PyTorch Experiments on NLP and RNN 7. TensorFlow on Mobile with Speech-to-Text with the WaveNet Model 8. Implementing GANs to Recognize Handwritten Digits 9. Sentiment Analysis over Text Using LinearSVC 10. What is Next? 11. Other Books You May Enjoy

Creating an iOS app to predict house prices

In this section, we are going to consume the model through the RESTful API via an iOS app. The purpose of this section is to demonstrate how a model can be consumed and used by an iOS app. Here, we have assumed that you are familiar with Swift programming. The same approach can be used for any similar use case. These are the following steps covered in this section:

  • Downloading and installing Xcode
  • Creating a new iOS project with a single screen
  • Designing the layout of the screen
  • Adding a functionality to accept input
  • Adding a functionality to consume the RESTful API that serves the model
  • Additional notes

Downloading and installing Xcode

You need a Mac (macOS 10.11.5 or later) to...

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